4.6 Article

Dynamical symmetries of Markov processes with multiplicative white noise

出版社

IOP Publishing Ltd
DOI: 10.1088/1742-5468/2016/05/053207

关键词

Brownian motion; driven di. usive systems (theory); fluctuations (theory); stochastic processes (theory)

资金

  1. NSF (Argentina) [DMR-115181, PICT-2012-0172, PIP CONICET 2012 0931]
  2. ECOS-Sud collaboration [A14E01]
  3. CNRS-CONICET collaboration [PICS 506691]
  4. bi-national collaboration FAPERJ/CONICET (Brazil-Argentina)
  5. FAPERJ
  6. CNPq
  7. CAPES

向作者/读者索取更多资源

We analyse various properties of stochastic Markov processes with multiplicative white noise. We take a single-variable problem as a simple example, and we later extend the analysis to the Landau-Lifshitz-Gilbert equation for the stochastic dynamics of a magnetic moment. In particular, we focus on the non-equilibrium transfer of angular momentum to the magnetization from a spin-polarised current of electrons, a technique which is widely used in the context of spintronics to manipulate magnetic moments. We unveil two hidden dynamical symmetries of the generating functionals of these Markovian multiplicative white-noise processes. One symmetry only holds in equilibrium and we use it to prove generic relations such as the fluctuation-dissipation theorems. Out of equilibrium, we take profit of the symmetry-breaking terms to prove fluctuation theorems. The other symmetry yields strong dynamical relations between correlation and response functions which can notably simplify the numerical analysis of these problems. Our construction allows us to clarify some misconceptions on multiplicative white-noise stochastic processes that can be found in the literature. In particular, we show that a first-order differential equation with multiplicative white noise can be transformed into an additive-noise equation, but that the latter keeps a non-trivial memory of the discretisation prescription used to define the former.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据